{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"6\" color=\"black\"><b>Bikeshare数据集上的模型训练</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"5\" color = \"red\"><b>导入工具包</b></font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd                               #导入结构化数据分析工具集\n",
    "import numpy as np                                #导入数值计算工具集\n",
    "\n",
    "#图表处理工具集\n",
    "import seaborn as sn                              #导入图表统计数据集\n",
    "import matplotlib.pyplot as plt                   #导入数据可视化工具集\n",
    "%matplotlib inline                                 \n",
    "#可以直接在你的python 控制台里面生成图像\n",
    "\n",
    "#设置参数\n",
    "params = {'legend.fontsize':'x-large',\n",
    "         'figure.figsize':(30,10),\n",
    "         'axes.labelsize':'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'x-large',\n",
    "         'ytick.labelsize':'x-large'}\n",
    "\n",
    "sn.set_style('whitegrid')                          #设置图表的自定义风格\n",
    "sn.set_context('talk')                             #设置绘图文本参数\n",
    "\n",
    "plt.rcParams.update(params)                        #手工修改了配置文件，希望重新从配置文件载入最新的配置\n",
    "pd.options.display.max_colwidth = 600              #设置最大显示列宽\n",
    "\n",
    "#将数据帧显示为表\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"5\" color=\"red\"><b>导入数据，查看数据信息</b></font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('day.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color = \"black\">具有离散型数据特征的字段有：season、yr、mnth、holiday、weekday、workingday、weathresit</font> <br><font size=\"4\" color=\"black\">具有连续型数据特征的字段有：temp、atemp、hum、windspeed</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"5\" color=\"red\"><b>数据探索</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\"><b>单数据分布规律</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">连续型特征：temp、atemp、hum、windspeed</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a2f3438>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "sn.distplot(df['casual'],bins=10,kde=False)\n",
    "#绘制字段casual（非注册用户贡献的骑行量）直方图,显示10个直条区间，显示直方图，不显示核密度估计。\n",
    "#从直方图可以看出，非注册用户贡献的骑行量，大部分集中在贡献骑行量低的一侧。表示非注册用户一般不怎么骑车。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a6049e8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.distplot(df['registered'],bins=10,kde=True)\n",
    "#绘制字段registered(注册用户贡献的骑行量)直方图，显示10个直条区间，显示直方图，同时也显示核密度估计。\n",
    "#从直方图可以看出，注册用户贡献的骑行量，呈现正态分布。表明注册用户大部分都贡献在中等水平，贡献骑行量特别多或者特别少的用户数都比较小众。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a2f9a90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.distplot(df['cnt'],bins=10,kde=True)\n",
    "#绘制字段cnt（总租车人数）直方图，显示10个直条区间，显示直方图，同时也显示核密度估计。\n",
    "#从直方图可以看出，总租车人数，呈现正态分布。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">非注册用户贡献的骑行量集中在0-1000，注册用户和总用户的数量形状与正态分布类似。</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a72db70>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "sn.distplot(df['temp'],bins=30,kde=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000025F6A79F7B8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000025F6A823710>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features=['atemp','hum']\n",
    "df[features].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a8be128>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.distplot(df['windspeed'],bins=10,kde=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6a951828>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_,axes= plt.subplots(1,2,sharey=True,figsize=(7,4))\n",
    "sn.boxplot(data=df['temp'],ax=axes[0])\n",
    "sn.violinplot(data=df['temp'],ax=axes[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">离散型特征：season、yr、mnth、holiday、weekday、workingday、weathresit</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    188\n",
       "2    184\n",
       "1    181\n",
       "4    178\n",
       "Name: season, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['season'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "sn.countplot(df['season'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">四个季节的数据量基本一致</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6aa143c8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['yr'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">两年的数据量基本一样</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6aa6da90>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['mnth'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6aaaafd0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['holiday'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6ab22f28>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['weekday'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6ab68198>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['workingday'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6abcd5c0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(df['weathersit'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\"><b>特征与特征之间的相关性</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size =\"4\" color= \"black\">猜测：atemp和temp之间是正相关，holiday和workingday是负相关</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size =\"4\" color=\"black\">用热度图表示不同特征的相关系数</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6ac4acf8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols=df.columns\n",
    "data_corr=df.corr()\n",
    "sn.heatmap(data_corr,annot=True)   \n",
    "#annot表示数据之间的相关性大小"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6ac0f6d8>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr=data_corr.abs()\n",
    "plt.subplots(figsize=(13,9))\n",
    "sn.heatmap(data_corr,annot=True)\n",
    "sn.heatmap(data_corr,mask=data_corr<0.5,cbar=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "instant and yr = 0.87\n",
      "instant and registered = 0.66\n",
      "instant and cnt = 0.63\n",
      "season and mnth = 0.83\n",
      "yr and registered = 0.59\n",
      "yr and cnt = 0.57\n",
      "workingday and casual = 0.52\n",
      "weathersit and hum = 0.59\n",
      "temp and atemp = 0.99\n",
      "temp and casual = 0.54\n",
      "temp and registered = 0.54\n",
      "temp and cnt = 0.63\n",
      "atemp and casual = 0.54\n",
      "atemp and registered = 0.54\n",
      "atemp and cnt = 0.63\n",
      "casual and cnt = 0.67\n",
      "registered and cnt = 0.95\n"
     ]
    }
   ],
   "source": [
    "size=data_corr.shape[0]\n",
    "col=cols.drop('dteday')  #去掉object型对象\n",
    "corr_list=[]\n",
    "threshold=0.5\n",
    "for i in range(size):\n",
    "    for j in range(i+1,size):\n",
    "        if data_corr.iloc[i,j]>threshold and data_corr.iloc[i,j]<1:\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j])\n",
    "for v,i,j in corr_list:\n",
    "    print('{} and {} = {:.2f}'.format(col[i],col[j],v))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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W8xneMPEZ3jDxGd4w8RneMPEZ3jDxGd4w8RneMPEZ3vg/qfErdnCX2PQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%config InlineBackend.figure_format='png'\n",
    "for v,i,j in corr_list:\n",
    "    sn.pairplot(df,x_vars=col[i],y_vars=col[j])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\"><b>特征与类别间的相关性</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">与年份有很大关系，yr=1的类普遍比yr=0的类数量多</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6c59a940>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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be1eS7jAoKSnhrrvuYsGCBVaH1mgJVcMohBBCiNTj9Xp5+umn+eyzzwBzab/beh0gOy0+q7VYZXhbH12a7eelVVnsqILnn3+ePXv2MH78eGzRXgA7xlIspxdCCCFEIqmtreX++++vSxZ/2rGG+/pXpnyyGJGXGeLRIeX0b+UD4K233uK5555LumUFJWEUQgghREwEAgEee+wxVqxYAcDVp1Rx7anVcV/az2puB9zdt5Lz25sTuyxcuJDp06djGMmTNEvCKIQQQoiYeOGFF/j2228BGNfzABd3riXJWmKjxmGHG1QVIzuYSePcuXOZO3euxVGdOEkYhRBCCBF1n3zyCQsXLgRgbLdqLuzotTgi69lsMK5nFae3MX8WM2fOZMOGDRZHdWIkYRRCCCFEVJWWlvLCCy8A0L+VjzFdayyOKHHYbXDTaQfIywgSCASYPHkygUDA6rCOSxJGIYQQQkTVP/7xDw4cOECmM8T4/ANNthn6aNwOuLVXJTYMtmzZwuLFi60O6bgkYRRCCCFE1FRWVjJ//nwALu5cSwt38gzsiKfu2UFOb2uOnP773/+e8ANgJGEUQgghRNQsXbqUmpoa0uwGF4QHeFhtd9XBdOedTRlsP+CwMJqDLulsNtVv27aNzZs3WxzNscnE3ULEUCAQoLi42OowoqL+daTKNeXm5uJ0ym1QiGj67rvvAMhv4SfTZX2t2fYDDv6yJqvu+dK9blaXunhwUAWdmgUtjAy6NAvS0h2k1Otg6dKldO/e3dJ4jkXulELEUHFxMVdffbXVYUTdxIkTrQ4hKubMmUNeXp7VYQiRUgoLCwHo2SIxBnJ8uD2d6sChDapVATsfbk9n/GlVFkVlstlAtQjwzR5H3c8tUUmTtBBCCCGipqSkBIBW6dbW3kWsL3c1aHu8tXSbK77s27fP4kiOTWoYhYiTSYPK624MySoYDt+RxB81S712Ji9rbnUYwiLLli3j1VdfZdSoUVx66aVWh5OSamrMfnkeh/XN0QD+o9x2j7Y93jxO8+dUXV1tcSTHJgmjEHHS0h0i15MgdyghmqgXX3yR7du3s3btWkkYYyQ9PZ2amhp8IZlL50T4wv8WPB6PtYEcRxLXEwghhBANs337dqtDSHnNmjUDoMInKcaJqAz/nDIzMy2O5Njk3RRCCNEkBYOJ0ccu1bRv3x6APTWSYpyIPTXmFD8dOnSwOJJjk3dTCCFEk7R//36rQ0hJXbp0AWDHAen1djyGQd2ckJ07d7Y4mmOThFEIIUSTcPh6vakyn2iiUUoBsLnSSSgxxr0krOJaO5V+MxXLz8+3OJpjk4RRCCFEk1BUVHTI8927d1sUSWrr3bs3ALVBG1srE2NFlUSl95tT+2RmZtbVzCYqSRiFEEI0CVu3bj3k+ZYtW6wJJMW1a9eurh/jmrLEmOswUa0pM5vtBwwYgMOR2Mm1JIxCCCGaBK31Ic/Xr19vUSSpb+DAgQCsLJWE8WhCBqwqTQMO/rwSmSSMQgghmoSVK1cCYNjMf32rVq2SkdIxMmzYMADW73dRmxgrBCac7QcclIen1In8vBKZJIxCCCFSXnV1NatWrQLA22EwAJWVlf9V6yiiY9CgQdjtdgKGTZqlj2LFPrN2sV27dnTq1MniaI5PEkYhhBAp76uvvsLv92PYHPjbKILpLQD47LPPrA0sRWVlZdGvXz8ACsKJkThUQYmZSI8YMQKbLfFXxUmoSZKUUg7gSeA3QDrwAXC71rpUKeUEngeuwYz7f4H7tNa+evtPAu4AsoD5wJ1a6/31ym8CJgFtgU+A27TWO+JxbUIIIazz3nvvARBo3hEcaQRadcexcxmLFi1i/PjxuN1uiyNMPcOHD6egoICCkjRCRhX2xM+J4qbCZ2NThZmCDR8+3OJoTkyi1TBOBm4ErgPOB/KBV8JlTwEXA6OBMeHvT0V2VErdDkwM738+0At4rV75JcCfgd8DwwEXME8pJb/CQgiRwlavXs2KFSsA8Lcx57rzt+6JYbNRXl7OBx98YGV4KeuMM84AYL/PzhaZXucQK/alYWDD4/EkxYAXSKAaRqVUNnA3cJXW+uPwtt8CM5RSWcDtwNVa62/CZROAOUqph7XWNcC9wB+11ovC5dcDPyqlOmutt4XLZ2it3wmXXwPsBs4CvojntcZKIBCIy0S0kU7isZ4CIDc3F6czYX5FhRBJyDAMZs6cCUAwoxXBZu0gFMJIy8Df6lTSStYza9YsLrzwwoRfyzfZdO7cmY4dO7Jjxw6Wl6TRPbvG6pASxrJwc/TQoUNJS0uOJvtE+m98NhAC3o9s0Fp/CvRUSg0HMoEl9V7/eXjbAKXUZqB7/XKt9UqlVBlwplJqB2at4tR65fuUUqtIkYQxEAgwbtw4du3aZXUoUdO+fXtmzZolSaMQotEWLlxYV7vo7TCIzNX/BKCqzxX42g/AVbqJffv28eqrr3L33XdbGWpKOuuss3j77bdZVpzGFd0lYQTwBWFluF/nmWeeaXE0Jy6R/hOfAmwDLlVKPQrkYvZhvAfoAFRprcsjL9ZaVyilqoGOQKQf487Djrk7XJ4DZByjvMGCwWBCja4LBoP4/X6rw4gqv9/P+vXrE34y02MpKSmpe1xam2g9QJqm+u9DYWEhFRUVJ7Rfqk2/kmj3sFjYtWsXU6ZMAcCf042QpwV2byUANn8VhjsLX/uBuHd8z7/+9S/y8vIYMGCAlSGnnMj6yNurnOypttM2IxT3GIyjLE94tO2xtrLUhS9kw26307p167j8HUbj/pVICWMW0B54BDNJDGL2OZwT/vIeYR8v4MZMBjnCa060POk5HA4ef/xxysrKYnqesrIy/vSnPwFw3333kZOTE7Nz5eTkJHWyCIf+kU5e3tzCSMSRpFoSKA4qLy/n5ZdfxufzEUrLpLbrGdiCvv96na9dHxzlO3BWFvHXv/6Ve++9l65du8Y/4BTVrVs3mjdvTnl5Od8Vp3Fpl9q4x+AL56i33HILY8eOZd68ecycObNue7x9t9dMO5RSNGvWzJogGiGREkY/ZtJ4g9Z6BYBSajzwA+aI5iMldm6gGqip97zyOOVH2r/BHA5H3QLrTUn9tVcHDx5MXl6ehdEkvoyMjOO/SFimW7duJzz/WUFBQUolmKl8DysuLmby5Mns27cPw+6k5pQLwOmGIySM2OzU9jifjDUL8PkO8PLLL/Pcc8+Rn58f/8BT1MiRI5k3bx7/2eO2JGEMGubY1rFjx+LxeBg7diwzZ86s2x5PvuDB/osXX3xx3P4Go3H/SqSEMdL5bnW9bWvD391AplIqS2tdCXWDZCLNzJGpcfKAknr754XL92EmhodnN3kc2i9SiKiq3/9y0sByWqZb9JFW1CmttdfV9kr/2NRTWFjIgw8+SFFREYbNTk2P8wlltj7mPobLQ03Pn+JZ928qKyu55557ePjhhxkxYkScok5tF1xwAfPmzWPrASc7qxx0yIzvBy+HzWx7njdvXl0NY/3t8VSwL43aoB2Hw8E555wT9/OfjES6W34d/j4IWBp+3Dv8/Z/AHzAHxiwMbzsXqAJWaK1rlVKF4fKVAEqpvkAL4ButtaGU+k+4fEG4vBXQB7grlhclRETL9BC5HkkYhYiVxYsX89xzz1FbW4thd1BzyoUEm3c4oX1DnhZUn3YJGes+oLq6igcffJAbb7yRa6+9Num7xlitd+/etGvXjqKiIr7c7eZXpzSqYa/R0sLdlmfOnFk3Yr7+9nj6YrfZ0Dl06FBatGgR/wBOQsL0wtdabwL+D3hdKTVCKTUYmAks1FqvBV4FXlZKna2UOgd4CZimtY7Ub08FnlBKjQrv+yYwNzylDsAUYIJS6tfhZHI2sFxrnfQjpIUQoimrrKxk8uTJPPnkk9TW1hJKy6Q6/9ITThYjjPTmVPe6jGBmLoZh8Prrr3P33Xen1OwTVrDZbFx88cUAfFnkJhDnz81HW0Ql3ourlHrt/LjPbI6+5JJL4nvyKEiYhDHseswpbt7H7Le4CnNlFzAn3P4Qs4bwn5gruUyqt+9UYDrwBrAYWAPcHCnUWs8Hfgc8DXyDObJ6bMyuRAghREwZhsGHH37IuHHj+OijjwBzJZfqXqMJZbZq3DHTMqjOvxhfm9MAWLlyJTfeeCNvvfVWys1EEU8XXXQRdrudcp+d74uTY97BaPtkpxsDGzk5OUnZ3SGRmqTRWlcB/xP+OrzMC9wW/jrSvgbwcPjraMd/GXg5KsEKIYSwzOrVq3nllVdYuXIlAIbdibfTUPy5+SdfdWR34u0ygkCLTqRv/hKvt5rXXnuNDz74gFtuuYWzzz47Kdb+TSRt27blrLPOYsmSJSzans7pbXxxr+Gzki8In+5MB+Cyyy7D5XJZHFHDJVTCKIQQQhxLYWEhb7zxBkuWHByv6M/pirfz6Rhp0V2pJdi8I1V9r8C9cxmuPWvYsWMHjzzyCL179+bGG29k8ODBkjg2wBVXXMGSJUvYVOFC73eSnxOwOqS4WbLbTaXfjsvl4vLLL7c6nEaRhFEIIUTCW79+PW+99dYhiWIwoxXeTkMJZreP3YkdLrydT8ef2xP39u9xlm9n9erV3HffffTu3Ztx48YxbNgwSRxPQL9+/ejTpw+rVq3iX1s8/D6n8vg7pQB/CN7b6gHMpvlWrRrXXcJqkjAKIYRISIZhsHTpUt555x2WLVtWtz2Y3hxf+4EEWnaL28iFkCeHmp4/wVGxm7Rdy3FWFrF69WoeeOABunXrxq9+9SsuuOCCpGxqjBebzcavf/1rHnjgAdaUpbGmzEmvJlDL+OnOdEq9DhwOB1dffbXV4TSaJIxCCCESSnV1NR9++KE5d9/WrXXbg54cfHn9CbTsCjZrxmwGs/Ooyc4zE8fdBTgrdrN582aeeeYZZs6cyejRo7nsssuSthYp1oYNG0bfvn1ZuXIl/9iUwaODK1K6L2NNAN7dYtYujho1ivbtY1gbHmOSMAohhEgIW7du5d133+WDDz6gqqqqbnsgOw9fu74EszvEfy6Uo4gkjvaqEtKKVuEs3UxpaSlvvPEGb731Fueddx6jR4+mb9++0lxdj81m45ZbbmHChAkUVrj4Zk8aZ7Q7wgo8KeK9rR4q/Hbcbjfjxo2zOpyTIgmjEEIIy/j9fr788kvmz59PQUFB3XbD5sDfqgf+tqcRykjc2rpQZmtqe5yHreMQXHvX4SrRBAJePv74Yz7++GO6devG6NGj+clPfpJU6wbHUt++fTn33HP5/PPP+cemDAbn+nCn4Nzoe2vsfLDdrF28+uqrad362CsOJTpJGIUQQsTdjh07eP/99/n3v//N/v3767aH3Fn4cxW+3J7gTLcwwoYx3M3wdRqCr8MAnPsKSSteh6OqhM2bNzNlyhRmzJjByJEjueyyy8jPz2/ytY633XYbX3/9NaVes8n2yh41VocUdX/fkIk/ZCM3N5errrrK6nBOmiSMQggh4iIQCPDll1+yYMECfvjhh7rtBjYCLTrhb5OfUM3OjWJ3EsjtSSC3J/aqErPWsbSQ2tpaFi5cyMKFCznllFMYPXo0F154IRkZGVZHbIm8vDyuueYa3nzzTf69zcNZeV7yMlJn6dSCEhfLS8wJyu+44w7S05Pnw8/RSMIohBAipvbu3cu7777LwoULKS0trdseSsvE37on/tyeUZ9DMRGEMlvj7XYW3k7DcJVuwrV3HY6aMjZu3MgLL7zA9OnTufDCCxkzZgw9evSwOty4u+aaa1i0aBFFRUX87/pMfte/Mqk/K0T4gvDWevP3edCgQZx77rkWRxQdkjAKIYSIOsMwWL58OfPmzeOrr74iFDJrjwxsBJt3xNdGEWze0bLRznHlTMPf5jT8ufnYq4pJK9Y49xVSU1PDggULWLBgAX379mXMmDGce+65OJ1N41+z2+1mwoQJTJo0iVWlaXxfnMbQNsk/AGbhNg97ax04nU7uuuuulOl+0DR+K4UQQsSFz+fjk08+Ye7cuWzatKlue8jpwZ/bE3+uwnA30cEfNhuhZm2obdYGOg3DVbIRV/E6HLXlrFy5kpUrV/LKK69wxRVXMGrUKLKysqyOOObOOOMMhg8fzrfffsvsDRn0a5XcA2BKauwsCE/SfeWVV9KlSxeLI4oeSRgXVU0tAAAgAElEQVSFEEKcNK/Xy4IFC3j77bcpKSmp2x5o1gZ/m14EcrqAPYkzgWhzuvG3642/bS8cFbtw7V2Lc/92iouLeeWVV3jzzTcZO3Ysv/zlL2nRooXV0caMzWbjzjvv5IcffmCf16ydG9steQfAvL0pA3/IRuvWrfn1r39tdThRJQmjEEKIRgsEAsyfP5+33nqLsrIyIDyIpWU3fG17E2qWa3GECc5mI9i8A8HmHbDVVpC2dw2u4vXU1NQwe/Zs/vnPfzJ27FiuvfbalJ2Wp2PHjlx55ZXMnj2b97d6OL99LS3chtVhNdiGcidL97oBuPXWW1NuQFMT6DwihBAiFr799ltuvPFGXnrpJcrKyjBsdnxt8qnqdyW1Pc6TZLGBjPRsvJ2Hc6D/r/B2GIThSKO2tpY5c+Zw3XXX8e677xIMBq0OMyauvfZaWrRogS9k45+bky/RMgx4e6MZt1KKCy64wOKIok8SRiGEEA1y4MABnn76aX7/+9+zfft2DGz4chVV/a7E2+WMpttHMVqcbnztB3Cg/y/NxNHuZP/+/bzwwgvcc8897N692+oIoy4zM5Prr78egC92uymuSa70ZGWpiw3l5jrit912G3Z7csV/Ik74ipRShUqp/5puXynVXim1N7phCSGEOBar7slbt27lpptuYtGiRQAEsvKo7n053q5npuTUOJZypOFrP4Cqvr/A3+oUAFasWMH48eNZunSpxcFF36hRo2jTpg1Bw1a3/nIyMAz412Yz3kGDBjFw4ECLI4qNY/ZhVEqNBs4KP+0KPK6Uqj7sZafEIC4hhBCHsfqevH79eu677z4qKiowbA68nYbib3Na0ky0ba8pr3vs3v49vvb9CWW0tDCiE2OkZVDb/Rz8LbuRvvlLqqur+cMf/sDDDz/MeeedZ3V4UZOWlsY111zDn//8Z77e4+YXPappnpb4fRk3VjjZWGHWLib7etHHcrxBLyuAu4HI3WAgUH+SJAM4AFwf/dBSRyAQoLi42OowoqL+daTKNeXm5jaZec9E0rPsnlxRUcFDDz1ERUUFIWc6NT1/SigzedbGtVeX4in8rO65q2wzzopdVOdfnBRJI0CwRSeqe1+OZ/0iqCnjqaeeonPnznTv3t3q0KLmoosu4vXXX6eiooLFO9L5effEHzH9wTZzFZf8/Hz69+9vcTSxc8z/klrrrcBIAKXU34C7tNYV8QgslRQXF3P11VdbHUbUTZw40eoQomLOnDnk5eVZHYYQx2XlPfm1115j7969GHYnNfkXE/LkxOO0UePaswZb8NBJoW1BL649a/B2O+soeyUeIy2D6vxLyFzzLj5vJc899xzTp0+3OqyoSU9P59JLL2X27Nks2e1mTLca7AlcgV3us7EsvATgFVdckTKTdB/JCVeraK1vVEo5lVKnAC4OfsKNlK+JdnBCCCGOLJ735JqaGj766CMAvB0GJV2yCOA4sKdB2xOa001t17PI0P9m7dq1bNy4kVNOSZ3eYaNGjWL27NmUeh2sKnXRr5Xf6pCO6usiN0HDRlZWFuecc47V4cTUCSeMSqlRwN+AVhx2Y8JsBpEZWU9Adf4lhJK9Y7gRXiA+iZf0svuqyFi30OowhGi0eN6Tt2/fTk2N2TQYaJWcax7bQkeejuZo2xNdMKsdIVcGdn8169atS6mEsUOHDvTv358VK1bw7Z60hE4Yv9ljzrs4cuRI3G63xdHEVkM6bj0FLAEeB6RZupFCaZkY7tRf7inRhSw4Z6k3eRPsiGD4B+dI4ktJhfchLG73ZK/XW/fYsEt/34Rgs0H4vfD5kn/95cOdf/75rFixgmUlaQRCVTgT8M92b42dLZXmezBy5EiLo4m9hvzlnwL8Smu9LlbBCJHKJi9rbnUIIrXE7Z7ctWvXuseOyiKCLTrF+pTiOGy+auxe83NCt27dLI4m+s4++2ymTJlCdcDOuv0u+rRMvFrGZcVm38WcnBz69OljcTSx15CcfSnQN1aBCCGEaJC43ZOzsrLqRn+mFa00J54TlkorWglAixYt6NWrl8XRRF+rVq3Iz88HYHmJ66SO5TpKpnO07SeqYJ+ZMI4YMQKHI/V75TWkhnEeMFMpdT6wnkOnckBr/ZdoBqaUegq4RmvdNfzcCTwPXIMZ9/8C92mtffX2mQTcAWQB84E7tdb765XfBEwC2gKfALdprXdEM24h6svNzWXOnDlWhxEVxcXFdSPjp06dSm5u8i/7luTXENd78nXXXceKFStwVhbhKlmPP1dF8/CiAewH9uLaY45puvLKK1O279yIESNYu3YtP+5LAw6fbvTE9WzuZ3f1fyd0PZs3vtayNgB6v5lCjRgxotHHSSYNSRh/C+wHLg5/gdmx2hb+HrWbk1JqMPA7YGe9zU+FzzsaSAPexLxB3hfe53ZgIjAO2AfMBF4DfhEuvwT4MzAeWAs8B8xTSg3TWsvHZRETTqczJafsyc3NTcnrSjJxuycDDB06lAsuuIDFixfj3votQU8OoWZtonkKcQJsvmo8Gz/BhkGPHj248sorrQ4pZoYNG8brr7/OnhoHxTV2cj2N633+0061fFecRnXgYJVipjPETzvVNjq2tftdBA0bdrudQYMGNfo4yaQhFbKnAm8B/5/WupvWuhtQjDlK79RoBaSUSgPeAL6uty0duB24V2v9jdb6c2ACcJtSKrJ+0L3AH7XWi7TW32NOXHuFUqpzvfIZWut3tNY/YtZU9ufgqglCCJFM4nJPru/uu++mY8eO2Iwgng0fY68pi8VpxNEEvHjWf4jdX01GRgYPPfQQaWlpVkcVM6eeeirZ2dkArCptfLN0p2ZBbu9VWff89DZeHhxUQadmjR8hvzocT69evcjMTPKZT05QQxLG54BrgU31tk3DTMyeiGJMjwAbgbn1tg0AMjFHBEZ8Ht42QCnVDuhev1xrvRIoA85UStmB4YeV7wNWIQmjECI5xeueXCcrK4unn36a7Oxs7IFaPPoDSRrjJVBLhv4AR00pDoeDRx99NCUHu9TncDjq1mVeXXZy/RjzMg/WTv6yR/VJJYv14xkyZMhJHSeZNKRJ+mpgrNb6m8gGrfUspVQh8A5m38CTopQaBNwC9CPclBzWAajSWtctBKq1rgivodqRg3136jdhA+wOl+cAGccob7BgMIjW+oReW1JS0phTiDgpLCykokJmijqe+r/HTfFnFgwm3Hx9J3VPbsg97HATJkzgxRdfpLq6Gs+6hdSc+lNCzZK6P2hCs/mq8OhFOGr3Y7fbGT9+PC1atGj0+5dMOnY0/0WvKXMRMkiIVV/KvDZ2VpnpU25ublK8D9G4fzWkhtGDuUbp4cqAk54vpF5T9O+01kWHFWcA3v/aydzmDpdzhNecaLkQQiSbmN6Tj6Vz587cc889ZGVlYQ94ydD/xrF/eyxP2WTZq8vIWPMejtr9OJ1Obr75ZgYPHmx1WHFz2mmnAXDAb2fbgcQYibwm3BztdrtTvpa3vobUMH4KPKuUulZrXQqglGoBTAY+i0IsDwM7tdZvHqGshiMndm7MoVM19Z5XHqf8SPs3mMPhQKkTGyUY6YMhElP37t1lAMcJqP973BR/ZgUFBYlWy3hS9+SG3MOORClFz549uf/++ykqKsKz4WO8nU/H3+Y0c1JpcdIc5TvwbPoUW9BPRkYGTzzxRJNqAgXo2bMn7dq1o6ioiNWlLrpmWf83uKrM7Dc6aNCgpJnSKBr3r4bUME4EegA7lVLrlFJrgV2YfQcnnFQUpuuA85VSB5RSBzCn0OkcfrwHyFRK1S2RopTK5mAzc2RqnMP/g+WFy/dhJoZHKxdCiGQT63vycXXu3Jlp06bRs2dPbBikb/sW99ZvIEmX20sYhoGraDWe9R9hC/pp3bo1U6ZMaXLJIoDNZqu77pUnMfAlWgzj4ACcpvZ+nHANo9Z6m1KqD/AT4DTMfoPrgQ+11tFYae08oP5vw3XATeHtO4Eq4GwgsgDwueFtK7TWteF+O2cDKwGUUn2BFsA3WmtDKfWfcPmCcHkroA9wVxRiP2E2X1U8TyeOQt4HkezicE8+Ia1atWLKlCk8/fTTLFmyhLTiddhr91Pb43wMl+f4B4iXo002nmiTkIcCpG/9BlfJBsCsYZs8eXKyzxl6UoYMGcJ7773H+v0uvEFwW9gyvb3KQbnPXhdXU9KgRUHDk2S/H/6KKq311vrPlVIlQEBrvTH8/FXgZaXU9ZjzjL0ETNNaRyZSmgo8oZTaChQBrwJztdbbwuVTgLeVUiuBAuBPwHKt9RfRvpbDBQKBuseZ6xYe45XCCvXfHyGSSSzvyQ3h8Xh47LHHmDVrFm+88QbOyiIyVr9LzSkjE2cwjGHWet5yyy2MHTuWefPmMXPmzLrticDmPYBn0yc4qswBZueffz4PPPAA6enpFkdmrcGDB2O32wmEQqwtczGgtXXLBK7cZ9ZrtW3bls6dOx/n1aklAZfzPqrfAx9i1hD+E3Mll/qjAKcC0zEHziwG1gA3Rwq11vMxJwN/GvgG89P42DjELYQQKc9ut3PDDTfw5JNP4vF4sPuryFi3EGfxeqtDMxlmpevYsWPxeDyMHTv2kO1Wc1TsJmPNuziqSrDZbNx888088sgjTT5ZBHM6p0hfwR/3WTvv5Irw+YcNG4atifXVbVANYzxprV8GXq733AvcFv460usNzIEzD5/oMePF6Tz4Y67KvwQjrWlM8pnIbL6qutre+u+PEOLknH322UyfPp2HHnqIHTt24NnyJb6qYrydh4PdwrZEm1k/Mm/evLoaxvrbLWMYuPasxr39O2wYNGvWjIcffpjTTz/d2rgSzPDhw1m1ahUr9rkwDGvGVVUHbGwod9bF09TIf8o4M9IyMdxZx3+hEEIkqa5du/LKK6/w9NNP89VXX5FWrHFUl1JzygUYaRnHP0As2MxkdebMmWZT9GHbLREMkL7lS1ylhQD06NGDJ598kvbt21sXU4IaPnw4r732GsW1DnZVO+iQGf+uBCv3mcsBulyuugnFm5JkapIWQgiRJJo1a8aTTz7Jb37zG2w2G46qYjLWzMdeuceagI5WJWVRs6LNW0nGuvfqksULL7yQadOmSbJ4FD169Kgb+LOs2JrR0stLzObogQMHkpFh0QcfC0nCKIQQIibsdjvjxo3j6aefJjMzE7u/hgz978Tp12gRR2WR2V+xuhS73c6dd97JpEmTpL/iMdhsNs444wwACizoxxgMwYrwgJcRI0bE/fyJQBJGIYQQMTV8+HBmzJhBly5dsBkhPFu+xL19aeJNaRMHzpIN5hrcAS/Z2dk8//zz/OIXv2hyAygaI5Iwbix3Uu6L789rfbmTqoCZMp155plxPXeikIRRCCFEzHXs2JFp06bVDRZIK1pF+qZPIdREprUyDNJ2LsOz+QtsRoiuXbsyY8aMJtkXrrEGDhyIx+PBwEZBSXxrGZeFz3fqqafSpk2buJ47UUjCKIQQIi6aNWvG5MmT+fnPfw6Aq2wLng0fQdC6efXiwjBwb/sW964CAIYOHcq0adOa3PKaJystLa1u9PiyOCaMhgHLis3znXXWWXE7b6KRhFEIIUTcOBwOJkyYwG23mTOkOSt241n/YeomjYaBe8tXpO1dC8DPfvazuj6douEiCduqUnPVl3jYXuWguNYcTd9Um6NBEkYhhBBxZrPZuOqqq7jvvvsAcB7Yg2fjYgglxiTa0eTevpS0EnOQz9ixY3nggQdk7teTcPrpp+NwOPCHbHGbxDtSu5iXl0ePHj3ics5EJAmjEEIIS1x66aX89re/BcBZsQv3tm9SaiCMa+860vasBuCyyy5j4sSJ2O3yb/dkZGVl1fX7XFYSn+l1Is3fZ555ZpMenCS/uUIIISxz+eWXM27cOADSijXO8LyEyc5evQ/3tm8BM9G4++67m3SyEU2RZuGCkjSCMa6ULqm1s6XSrBFuyv0XQRJGIYQQFrvhhhvq5rZL3/oNNn+NxRGdJCNEeuESbEaIjh07MmnSJBwOC1eUSTGRhLEqYK9bqi9WCsK1mNnZ2fTp0yem50p0kjAKIYSwlN1u5/777yc7Oxtb0EdaeDRxsnKVbMRRU4bNZuPBBx9skquCxFKbNm049dRTgYOrr8RK5PjDhw9v8n1PJWEUQghhuZycHH79618D4CpeDwGvxRE1kmHgKloFmMv99erVy+KAUlM8Vn2pDcDaMtch52vKJGEUQgiREEaNGoXH48FmBHGVbbE6nEaxV+/DUbsfgF/+8pcWR5O6IhPA7652sKc6NqnM6jIXAcOGw+FgyJAhMTlHMpGEUQghRELIyMio+8fsqCyyOJrGicTdrl27umZTEX1KKXJycgD4sTQ2tYyRaXv69u1Ls2bNYnKOZCIJoxBCiIQRSbLstRUWR9I4kbglWYwtu93O0KFDAfhxX/Sn1zGMg8eNrC7T1EnCKIQQImFkZWWZD4I+awNpJFs47rrrEDETSRjXlrnwR3l6naJqO/u85sh2aY42ScIohBAiYVRXV5sP7Mk5ItUIx11Tk+RTAyWBwYMHA+AL2aI+vc6qMrM5Oicnp0mv7lKfJIxCCCESxrZt2wAIuZOzhs4Ix71161aLI0l9LVu2rEvm1pRGt1l6dfh4gwcPltV5wuSnIIQQIiEYhsHy5csBCGbmWhxN4wQzWwOwefNmysrKLI4m9UVqGVeVRS9hDIZgbZnzkOMLSRiFEEIkiNWrV7N3714Agi06WhxN4wSz2mHYnRiGwWeffWZ1OCkvktBtrnBS5Y/O0oubK53UBO2HHF9IwiiEECJBvPvuuwAEM1oR8uRYHE0j2R34W3YDzOsxDMPigFJbv379cDqdGNhYtz86/RjXhGsrO3XqRJs2baJyzFQgCaMQQgjL7d69m8WLFwPgb3OaxdGcnEj8mzdv5ptvvrE4mtTm8XjqVtNZE6Vm6Uj/xUGDBkXleKlCEkYhhBCWe/PNNwkGg4RcGfhbJfeo1FBmawLZHQB4/fXXCYWiPOeLOERdP8YoDHzxBqkbcS3N0YdKqHkLlFIdgReB84EA8D5wr9Z6v1IqG5gGXAbUAn8BntRaG+F9ncDzwDWY1/W/wH1aa1+9408C7gCygPnAnVrr/XG6PCGEEEewadMmFi1aBICv/QCwOyyO6OR5OwzCWbGTjRs3snjxYn7yk59YHVLKGjJkCH/729/YXe1kX62dVumNT9D1fnM5QLvdzsCBA6MYZfJLmIRRKeXATOL2YiaMHmA68CZwOfAa0Ak4L/z9TaAUeDl8iKeAi4HRQFq43AfcFz7+7cBEYBywD5gZPuYvYn1t9dl9VST9Z00jfAW25K2gtvuqrA5BCBH2yiuvYBgGwfTm+Fv3tDqcqAg1y8Wf0xVX2RZeffVVzjnnHNxut9VhpSSlFJmZmVRVVbGq1MW57b2NPtbKcC1lfn6+TL5+mIRJGIGBwCAgT2tdBKCUmgh8qZTqgpnY9ddarwQKlFKPAr8FXlZKpQO3A1drrb8J7zsBmKOUelhrXQPcC/xRa70oXH498KNSqrPWelu8LjJj3cJ4nUoIIRLe0qVL+e677wDwdhwKKTTnnbfjEJz7t7F3717+3//7f1x77bVWh5SSnE4ngwcPZsmSJfy47+QSxshygJFVZMRBifSXuRm4OJIshkWGl40AysPJYsTnQHelVB4wAMgElhxWngkMUEq1A7rXLw8fqww4M9oXIoQQ4vhCoRCvvvoqAIGsdgRbdIrZuYyjNHMfbXtUzpmeXTcAZvbs2VRUJOf62Mlg2LBhAKwucxFsZDNecY2d3dXOQ44nDkqYGkat9T7gg8M2/xbYCHQAdh5Wtjv8vWO4vEprXV7veBVKqepweaQf45GOEfPJvnJzc5kzZ06sTxMXxcXFTJw4EYCpU6eSm5uck+vWlwrXIEQy+uqrr9iwYQMQrl20RWcevSMJNmuLo7b8iNtjydu+P66S9VRVVfF///d/3HjjjTE9X1N1+umnA1AdsLOh3El+TqDBx1gRrl3Mzs4mPz8/qvGlgoRJGA+nlHoAuAJzkMsg4PA65shzN5BxhPLIayLlHOE1kfIGCwaDaK0bs2tSq6ysPORxKvTJkU/9J6akpKTucWFhYZP7uQWDQatDiKpEuIe98cYbAASadyTULLYf3Pxte+Eq24ItWDcOEsPhxt+2V0zPizMdX5teuHevYO7cuQwdOhSXK7rL2AlTp06d2L59OwX70hqVMBbsM9ePPu2009i4cWO0w7NUNO5fidQkXUcp9TDwDHC31vp9oIb/Tuwiz6uPUh55TaScI7wmUi6EECKOioqK2LRpEwC+dn1ifr5QRktqup9X99zfshvV+RcTymgZ83P72/bCsNmorq6moKAg5udrqvr0MX+Plpc0PCH3BmFteB7Hvn37RjWuVJFwNYxKqT9jjma+XWs9Pbx5B5B32Esjz3dhjorOVEplaa0rw8fJxqxZ3BneP7JPyWHHOLyZ+oQ4HA6UUo3ZNallZ2fXPe7evTt5eYe/LSJVNfX3vqCgIKVqGa2+h0USp5Ark2BWfH6XQp7mdY+9HYdguOMzCtZweQhmd8RZvp0tW7Zw3XXXxeW8Tc3o0aP597//ze5qJ3uq7bTNOPHOjKtKXfhDNhwOB2PGjKFZs2YxjDT+onH/SqgaRqXUE8AE4Pp6ySLA10BLpVT9toNzgcLwIJkVQBVw9mHlVcCK8GsK65crpfoCLQCZhl8IIeJszZo1AASz82LadzFRBLLbAwevW0SfUoqWLc0a4+UlaQ3aN/L6/v37p1yyGC0JU8OolBoITAL+BHwUHtkcsQv4FzBLKXUrZs3g4+HXo7WuUUq9ijnFzvWADXgJmKa1rg0fYyrwhFJqK1AEvArMjeeUOkIIIUx79+4FIJSefZxXpobIdUauW0Sf3W5n+PDhLFy4kOUlaVzUufb4OwEhAwrCCeOIESNiGWJSS6Qaxisw47kfc/Ry/a984DfAJsypcV4FXjisFvL3wIfAAuCfmJOAT6pXPhVzIvA3gMXAGuDmmF2NEEKIo7Kn0HyLDdFUrztezjjjDAB0uZMq/4nVXG+ucFLhtx+yv/hvCVPDqLV+CHjoOC/71TH29wK3hb+OVG4AD4e/hBBCWCgynZW9pmmszhq5ztatW1scSWobNGgQLpcLv9/PqlIXp7f1HXefgvB0Op07d6ZDhw6xDjFpyUcdIYQQcRcZieos3wHBhk+BkmxcZVsB6Nevn8WRpLaMjAwGDBgAHFy15Xh+DE+nM3z48JjFlQokYRRCCBF3I0eOxOVyYQv6cBWvtTqcmHJU7MJRZfZd/NnPfmZxNKkvskrLj6VpGMaxX1vhs7G5UlZ3ORGSMAohhIi7nJwcRo0aBYB753JstSk6EXzQT/rWrwFznsBI7ZeInUjiV+6zs7Pq2Es/rgnPveh2u2X+xeOQhFEIIYQlxo8fT8uWLbGFAng2Loag3+qQosswSN/8BfbaChwOB7/97W+xNYEphKzWuXPnur6iq8qO3Sy9utQs79evX0qsXBZLkjAKIYSwRFZWFo888gh2ux1HTRmeDR9DKEX6MxoG7m3/wVW2BYA777yTHj16WBtTE2Gz2Rg0aBAA646TMK7db5ZHXi+OThJGIYQQlhkwYAD33nsvAM7K3WbSmOw1jYaBe9u3pO01J+keM2YMY8aMsTiopqV///4A6P1OQkfpx1jqtbO3xmyylq4CxycJoxBCCEuNGjWKO+64AwBnxS4y9AfY/DUWR9VIoSDphZ+TttccyHPRRRcxceJEaYqOs0jCWBWws7v6yP0YN+w3B7ukp6dz6qmnxi22ZCUJoxBCCMtdeeWV3HvvvdhsNhxVxWSsfS/p5mi0+WvxrF+Eq7QQMGsW77//fpms2wIdOnSgRYsWAKzff+QppzeUm9tPO+00nM6EmZY6YclvsRBCiIRw2WWX8cQTT+B2u7F7K8lYswDH/uRYvdVeXUrGmndxVhYBcPPNN3PXXXdJsmgRm81G7969ASisOHIyuCm8vVevXnGLK5nJb7IQQoiEcfbZZzNlyhRat26NLeTHs+Fj0nYVcNwJ9Szk3Fdo1oj6DpCens5jjz3GtddeK83QFlNKAVBY+d8JYyAE2w6Y2/Pz8+MaV7KShFEIIURCyc/PZ8aMGfTu3Rsb4N65DM/GjyHgtTq0Qxkh3NuW4in8DFsoQNu2bXnppZc477zzrI5McDAR3FnlwB86tGxXlQN/yEzoI4mlODZJGIUQQiScVq1a8eKLLzJ69GgAnPu3k7lmAfbqUosjM9n8NXj0B6TtWQWY07LMmDFDBk8kkMh7ETJs/zXwZUu41rFFixZ165qLY5OEUQghREJKS0vjnnvu4YEHHsDlcmH3VpCx9j2c+wotjct+YC8Zq+fX9Ve8+uqrefbZZ+sGWYjEkJOTUzeB967DVnzZdsB8fsopp0jXgRMkCaMQQoiEdvHFFzNt2jTatm1rrgpT+BnubUvBCB1/5yhzFWsy1i3E7q8mIyODJ554gltvvVVG2Sao7t27A7DrsBrG7eH+izKZ+omThFEIIUTC69mzJzNnzmTIkCEApO1ZhWf9h/Hr1xgK4d7yNelbvsJmhOjcuTPTp0/nnHPOic/5RaNEEsaiw2oYd4SfR8rF8UnCKIQQIik0b96cZ555hquuugowJ/nOXLMg9vM1BmrxrP+AtOJ1AJx55plMnz6dLl26xPa84qR17doVgKKagwnjAb+NSr/9kHJxfJIwCiGESBpOp5PbbruNhx566JB+jY6K3TE5n622nMw179X1Vxw3bhxPPvkkmZmZMTmfiK5IQlgVOJju7Kk++Lhz587xDilpScIohBAi6Vx44YVMnTqVnJwcbEEfnvWLcO7bFNVz2A/sNedX9Fbgcrl45JFH+M1vfiOTcSeRIyWEe2rN2sa2bdvi8XjiHVLSkt96IYQQSem0005j+vTpdO3aFZsRwlP4Oa6i1VE5tqN8Bxn6A9tEH8gAAAqYSURBVOwBL82bN+fPf/4zI0eOjMqxRfxkZGTQqlWrQ7YVh5unO3XqZEVISUsSRiGEEEmrXbt2vPTSS/Tv3x+A9O3/MVeGOQnOsq14NnyMLRQgLy+PadOm1S0zJ5JPx44dD3leUms/4nZxbDIPQAoJBAIUFxfH9Bz1jx/rc+Xm5spUFSdI3nvRlGVlZfHss8/y6KOP8u233+LeuQyw4Wvfv8HHcpRtI33TJ9gMg65du/L888//Vw2VSC4dOnRgxYoVdc/3hRPG9u3bWxVSUpI7cooIBAKMGzeOXbt2xe2cEydOjOnx27dvz6xZsyRxOA5574UAt9vNk08+yRNPPMEXX3yBe+cP/P/t3V2IVOcdx/Hv7Mzszu66iq7VhNSYVPRpQi3SghGKzUsvYkMJKVVqQ1CkKSxCDMQGQnMTJBhK8KIm6U2goIm2gd6FFhMKxbQ0kpayItI+Jqmh0RZNNolW19fZ6cWsZtfo2ZmdcY4z5/sB2T3PjsuPffnz2/NayRe5MP/Omj9H/uR/6R0vi4sWLWLbtm3ejLsD3HzzzZO2Pxk/h9HCWB8PSUuSOsKlC1NWrFgBQM+/91H45IPLH68U+xnrGWCsZ4BKcfJVzl2jn1QPQ1fGWLhwoWWxg9x0000A5Kgwt1TmQiU3aV218c/3DlEoFNi5c+d1P1QIUC6XAcjn81O8sjEelqyN33vpc8VikWeeeYbNmzdz8OBBSoffYrQ0k7G+OdDVxemv/aD6wolXOl88S+97fyA3doG5c+fy/PPPWxY7yPz58wGokOPHXz3Fz4dnTVpXbZzIHaRQKHxh17uywe+99LlSqcSzzz7L0NAQx44do/T+Hxm980HIFycXRYBKhd7Df6Lr3Cl6enp47rnnmDdvXjrBdV1M/H5+8L9q7SmVSsyYMSOtSG0pU4ekQwiFEMIvQggfhRA+DSFsDyF0p51LahcjIyNs2rSJkZGRtKNIiWbPns2WLVsoFArkz56g58hfr/q64seHKHz2IQBPPPEEixcvbmVMtcDg4CC5XPUw9L9OVgvjvHnzLq+pNpkqjMBW4LvAg8BD42+3pppIaiM7duzgwIED7Ny5M+0o0pRCCDz66KMAFI//k65Txyd9PHfhDD0fVovkfffdx/3339/yjLr+isXi5VMMDo/vYfTK9/plpjCGEErARmBzjPHtGONe4DFgKITgrd6lKYyMjLBnzx4qlQp79uxxL6PawurVq1m8eDE5oPThO1CpXP5Y93+GyZXPMzAwcN2v/Fe65syZA8DH41dIWxjrl5nCCCwD+oG3JqztHV9blkoiqY3s2LGDsbExoHrxi3sZ1Q4KhQIbN24EIH/qOPmT1dtP5c6PUvwoAtXnQ3uRS2ebPXv2pG2/3/XL0kUvtwCnY4wnLi3EGE+GEEaBum/3Xi6XiTE2M590Q3vzzTe5ePEiUL334xtvvMEDDzyQcqrWuXSFeKfI0gzr6+tjyZIlHDp0iO5jBzkz6xaKx/9BrjLGwMAAd9xxR2a+Fll15fO/s/TzD82ZX1naw9gHnLvK+jmgp8VZpLazfPnyy7fTyefz3HXXXSknkmp37733ApA/cZTc+dMUR94DYOXKlRSLxTSjqQWuvCLaK6Trl6U9jGe4ejHsAUbr/WT5fJ4QQsOhpHbx+OOPs2/fPsrlMoVCgU2bNmXqPKDh4eGO2suYtRl2++23s2vXLk6dOkX30b/Tdf40AGvXruXWW29NOZ2ut9tuu23S9pIlSzL189+M+ZWlPYxHgP4QwsClhRDCTKp7Ho+mlkpqE4ODg6xatYpcLseqVasyVRbV/rq7u1m+fHn1/Y/fBWDBggWWxYwYGBhI3NbUslQY9wOngZUT1u4eX9t/1f8haZL169ezdOlS1q1bl3YUqW7Lli1L3FbnsjA2LjOHpGOMZ0IILwMvhhDWAzngBeClGOPZdNNJ7WFwcJDt27enHUOalisPQWbpkGTWeQ5j4zJTGMc9BfQCrwMXgV3A06kmkiS1xMKFCxO31bmuLIj9/f0pJWlfmSqMMcZzwND4P0lShpRKpUnbPn89O/r6+hK3NbUsncMoScq4S7eGgi/ezFmd68qCeOV9GTU1v2KSpMzYsGEDuVyOe+65Z1J5VGfr7fUJwI3K1CFpSVK2PfLII6xZs4aeHp/XkCUWxsa5h1GSlCmWxezxaT6NszBKkqSOlsvl0o7Q9iyMkiRJSmRhlCRJUiILoyRJkhJZGCVJkpTIwihJkqREFkZJkiQlsjBKkiQpkYVRkiRlxqxZs9KO0JYsjJIkqeMNDQ3R29vLk08+mXaUtuSzpCVJUsdbu3Yta9asIZ/Ppx2lLbmHUZIkZYJlcfosjJIkSUpkYZQkSVIiC6MkSZISWRglSZKUyMIoSZKkRN5WZ3pmlstlhoeH084hqUXK5TLAzLRzNIkzTMqQZswvC+P0jAFd5XL5ZNpBJLXMTKq/+53AGSZlS8PzK1epVJqURZIkSZ3IcxglSZKUyMIoSZKkRBZGSZIkJbIwSpIkKZGFUZIkSYksjJIkSUpkYZQkSVIiC6MkSZISWRglSZKUyMIoSZKkRBZGSZIkJSqkHUDtI4RQALYBD1P92XkF+GmM8XyqwdQyIYQc8HvgdzHGF9POI9XDGZZtzq/GuIdR9dgKfBd4EHho/O3WVBOpZUIIXcALwKq0s0jT5AzLKOdX4yyMqkkIoQRsBDbHGN+OMe4FHgOGQgi96abT9RZC+AqwF/ge8FnKcaS6OcOyy/nVHBZG1WoZ0A+8NWFt7/jaslQSqZVWAAeAbwAnUs4iTYczLLucX03gOYyq1S3A6Rjj5V+2GOPJEMIo8OX0YqkVYoy7gd0AIYSU00jT4gzLKOdXc7iHUbXqA85dZf0c0NPiLJJUL2eY1AALo2p1hqsP1R5gtMVZJKlezjCpARZG1eoI0B9CGLi0EEKYSfWv9qOppZKk2jjDpAZYGFWr/cBpYOWEtbvH1/ankkiSaucMkxrgRS+qSYzxTAjhZeDFEMJ6IEf1nlYvxRjPpptOkpI5w6TGWBhVj6eAXuB14CKwC3g61USSVDtnmDRNuUqlknYGSZIk3cA8h1GSJEmJLIySJElKZGGUJElSIgujJEmSElkYJUmSlMjCKEmSpEQWRkmSJCWyMEqSJCmRhVGSJEmJfDSgdA0hhF8CS2OMKyesrQO2UH0O7WvA2vH3vx5j/DSVoJJ0Fc4wNZN7GKVrexX4VghhwYS1h4HdQAX4CbAa+L6DVtINyBmmprEwStcQY/wLcBj4IUAI4UvAd4Bd4y95Lcb4TozxbylFlKRrcoapmSyMUrJXqR6ygerQPRhjPDi+/X46kSSpZs4wNYWFUUr2KvDNEMIi4Ed8/pc5wJl0IklSzZxhagoLo5Qgxvgu8A6wAVgO/DrdRJJUO2eYmsXCKE3tFWAz8OcY45G0w0hSnZxhapiFUZrab4BuJh/KkaR24QxTw7wPozS1+cB54LeXFmKMt6WWRpLq4wxTwyyM0jWEEOYB3wYeA3bHGD9LOZIk1cwZpmbykLR0bTOAXwG9wM9SziJJ9XKGqWlylUol7QySJEm6gbmHUZIkSYksjJIkSUpkYZQkSVIiC6MkSZISWRglSZKUyMIoSZKkRP8H2MpjD0Ue4h8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_,axes=plt.subplots(1,2,sharey=True,figsize=(10,4))\n",
    "sn.boxplot(x='yr',y=\"cnt\",data=df,ax=axes[0])\n",
    "sn.violinplot(x=\"yr\",y=\"cnt\",data=df,ax=axes[1])  #axes控制着图片展示在哪个子图中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25f6c657c88>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_,axes=plt.subplots(1,2,sharey=True,figsize=(10,4))\n",
    "sn.boxplot(x='season',y=\"cnt\",data=df,ax=axes[0])\n",
    "sn.violinplot(x=\"season\",y=\"cnt\",data=df,ax=axes[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"5\" color=\"red\"><b>特征工程</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\"><b>数据分离</b></font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=df['cnt']   #将字段cnt从数据表中分离出来\n",
    "X=df.drop('cnt',axis=1)\n",
    "\n",
    "log_y=np.log1p(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color =\"black\" >将dteday中的日期提取出来，看是否与最终的结果有关</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "day=df['dteday']\n",
    "for i in range(len(day)):\n",
    "    day[i]=day[i][-2:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">离散型数据处理（season、mnth、weekday、weathersit）均为数值型，可以用get_dummies进行独热编码</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['season'].astype('object')\n",
    "x_season=X['season']\n",
    "x_season=pd.get_dummies(x_season,prefix='season')\n",
    "\n",
    "X['mnth'].astype('object')\n",
    "x_mnth=X['mnth']\n",
    "x_mnth=pd.get_dummies(x_mnth,prefix='mnth')\n",
    "\n",
    "X['weekday'].astype('object')\n",
    "x_weekday=X['weekday']\n",
    "x_weekday=pd.get_dummies(x_weekday,prefix='weekday')\n",
    "\n",
    "X['weathersit'].astype('object')\n",
    "x_weathersit=X['weathersit']\n",
    "x_weathersit=pd.get_dummies(x_weathersit,prefix='weathersit')\n",
    "\n",
    "features=['season','mnth','weekday','weathersit','dteday']\n",
    "X=X.drop(features,axis=1)\n",
    "X['day']=day\n",
    "feat_name=X.columns\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">连续值标准化处理（StandardScler）</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "ss_X=StandardScaler()\n",
    "ss_y=StandardScaler()\n",
    "ss_log_y=StandardScaler()\n",
    "\n",
    "X=ss_X.fit_transform(X)\n",
    "y=ss_y.fit_transform(y.values.reshape(-1, 1))\n",
    "log_y=ss_log_y.fit_transform(log_y.values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>yr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>...</th>\n",
       "      <th>weekday_2</th>\n",
       "      <th>weekday_3</th>\n",
       "      <th>weekday_4</th>\n",
       "      <th>weekday_5</th>\n",
       "      <th>weekday_6</th>\n",
       "      <th>weathersit_1</th>\n",
       "      <th>weathersit_2</th>\n",
       "      <th>weathersit_3</th>\n",
       "      <th>cnt</th>\n",
       "      <th>log_cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.729683</td>\n",
       "      <td>-1.001369</td>\n",
       "      <td>-0.171981</td>\n",
       "      <td>-1.471225</td>\n",
       "      <td>-0.826662</td>\n",
       "      <td>-0.679946</td>\n",
       "      <td>1.250171</td>\n",
       "      <td>-0.387892</td>\n",
       "      <td>-0.753734</td>\n",
       "      <td>-1.925471</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.817953</td>\n",
       "      <td>-2.387564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.724944</td>\n",
       "      <td>-1.001369</td>\n",
       "      <td>-0.171981</td>\n",
       "      <td>-1.471225</td>\n",
       "      <td>-0.721095</td>\n",
       "      <td>-0.740652</td>\n",
       "      <td>0.479113</td>\n",
       "      <td>0.749602</td>\n",
       "      <td>-1.045214</td>\n",
       "      <td>-1.915209</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.912999</td>\n",
       "      <td>-2.742332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.720205</td>\n",
       "      <td>-1.001369</td>\n",
       "      <td>-0.171981</td>\n",
       "      <td>0.679706</td>\n",
       "      <td>-1.634657</td>\n",
       "      <td>-1.749767</td>\n",
       "      <td>-1.339274</td>\n",
       "      <td>0.746632</td>\n",
       "      <td>-1.061246</td>\n",
       "      <td>-1.556689</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.629925</td>\n",
       "      <td>-1.847887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.715466</td>\n",
       "      <td>-1.001369</td>\n",
       "      <td>-0.171981</td>\n",
       "      <td>0.679706</td>\n",
       "      <td>-1.614780</td>\n",
       "      <td>-1.610270</td>\n",
       "      <td>-0.263182</td>\n",
       "      <td>-0.389829</td>\n",
       "      <td>-1.078734</td>\n",
       "      <td>-1.412383</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.519898</td>\n",
       "      <td>-1.596254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.710728</td>\n",
       "      <td>-1.001369</td>\n",
       "      <td>-0.171981</td>\n",
       "      <td>0.679706</td>\n",
       "      <td>-1.467414</td>\n",
       "      <td>-1.504971</td>\n",
       "      <td>-1.341494</td>\n",
       "      <td>-0.046307</td>\n",
       "      <td>-1.116627</td>\n",
       "      <td>-1.371336</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.500269</td>\n",
       "      <td>-1.554995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    instant        yr   holiday  workingday      temp     atemp       hum  \\\n",
       "0 -1.729683 -1.001369 -0.171981   -1.471225 -0.826662 -0.679946  1.250171   \n",
       "1 -1.724944 -1.001369 -0.171981   -1.471225 -0.721095 -0.740652  0.479113   \n",
       "2 -1.720205 -1.001369 -0.171981    0.679706 -1.634657 -1.749767 -1.339274   \n",
       "3 -1.715466 -1.001369 -0.171981    0.679706 -1.614780 -1.610270 -0.263182   \n",
       "4 -1.710728 -1.001369 -0.171981    0.679706 -1.467414 -1.504971 -1.341494   \n",
       "\n",
       "   windspeed    casual  registered    ...     weekday_2  weekday_3  weekday_4  \\\n",
       "0  -0.387892 -0.753734   -1.925471    ...             0          0          0   \n",
       "1   0.749602 -1.045214   -1.915209    ...             0          0          0   \n",
       "2   0.746632 -1.061246   -1.556689    ...             0          0          0   \n",
       "3  -0.389829 -1.078734   -1.412383    ...             1          0          0   \n",
       "4  -0.046307 -1.116627   -1.371336    ...             0          1          0   \n",
       "\n",
       "   weekday_5  weekday_6  weathersit_1  weathersit_2  weathersit_3       cnt  \\\n",
       "0          0          1             0             1             0 -1.817953   \n",
       "1          0          0             0             1             0 -1.912999   \n",
       "2          0          0             1             0             0 -1.629925   \n",
       "3          0          0             1             0             0 -1.519898   \n",
       "4          0          0             1             0             0 -1.500269   \n",
       "\n",
       "    log_cnt  \n",
       "0 -2.387564  \n",
       "1 -2.742332  \n",
       "2 -1.847887  \n",
       "3 -1.596254  \n",
       "4 -1.554995  \n",
       "\n",
       "[5 rows x 39 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fe_day=pd.DataFrame(data=X,columns=feat_name,index=df.index)\n",
    "fe_data=pd.concat([fe_day,x_season,x_mnth,x_weekday,x_weathersit],axis=1,ignore_index=False)\n",
    "\n",
    "fe_data['cnt']=y\n",
    "fe_data['log_cnt']=log_y\n",
    "fe_data.to_csv('FE_day.csv',index=False)\n",
    "\n",
    "fe_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 39 columns):\n",
      "instant         731 non-null float64\n",
      "yr              731 non-null float64\n",
      "holiday         731 non-null float64\n",
      "workingday      731 non-null float64\n",
      "temp            731 non-null float64\n",
      "atemp           731 non-null float64\n",
      "hum             731 non-null float64\n",
      "windspeed       731 non-null float64\n",
      "casual          731 non-null float64\n",
      "registered      731 non-null float64\n",
      "day             731 non-null float64\n",
      "season_1        731 non-null uint8\n",
      "season_2        731 non-null uint8\n",
      "season_3        731 non-null uint8\n",
      "season_4        731 non-null uint8\n",
      "mnth_1          731 non-null uint8\n",
      "mnth_2          731 non-null uint8\n",
      "mnth_3          731 non-null uint8\n",
      "mnth_4          731 non-null uint8\n",
      "mnth_5          731 non-null uint8\n",
      "mnth_6          731 non-null uint8\n",
      "mnth_7          731 non-null uint8\n",
      "mnth_8          731 non-null uint8\n",
      "mnth_9          731 non-null uint8\n",
      "mnth_10         731 non-null uint8\n",
      "mnth_11         731 non-null uint8\n",
      "mnth_12         731 non-null uint8\n",
      "weekday_0       731 non-null uint8\n",
      "weekday_1       731 non-null uint8\n",
      "weekday_2       731 non-null uint8\n",
      "weekday_3       731 non-null uint8\n",
      "weekday_4       731 non-null uint8\n",
      "weekday_5       731 non-null uint8\n",
      "weekday_6       731 non-null uint8\n",
      "weathersit_1    731 non-null uint8\n",
      "weathersit_2    731 non-null uint8\n",
      "weathersit_3    731 non-null uint8\n",
      "cnt             731 non-null float64\n",
      "log_cnt         731 non-null float64\n",
      "dtypes: float64(13), uint8(26)\n",
      "memory usage: 92.9 KB\n"
     ]
    }
   ],
   "source": [
    "fe_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"5\" color=\"red\"><b>训练分类器</b></font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 39 columns):\n",
      "instant         731 non-null float64\n",
      "yr              731 non-null float64\n",
      "holiday         731 non-null float64\n",
      "workingday      731 non-null float64\n",
      "temp            731 non-null float64\n",
      "atemp           731 non-null float64\n",
      "hum             731 non-null float64\n",
      "windspeed       731 non-null float64\n",
      "casual          731 non-null float64\n",
      "registered      731 non-null float64\n",
      "day             731 non-null float64\n",
      "season_1        731 non-null int64\n",
      "season_2        731 non-null int64\n",
      "season_3        731 non-null int64\n",
      "season_4        731 non-null int64\n",
      "mnth_1          731 non-null int64\n",
      "mnth_2          731 non-null int64\n",
      "mnth_3          731 non-null int64\n",
      "mnth_4          731 non-null int64\n",
      "mnth_5          731 non-null int64\n",
      "mnth_6          731 non-null int64\n",
      "mnth_7          731 non-null int64\n",
      "mnth_8          731 non-null int64\n",
      "mnth_9          731 non-null int64\n",
      "mnth_10         731 non-null int64\n",
      "mnth_11         731 non-null int64\n",
      "mnth_12         731 non-null int64\n",
      "weekday_0       731 non-null int64\n",
      "weekday_1       731 non-null int64\n",
      "weekday_2       731 non-null int64\n",
      "weekday_3       731 non-null int64\n",
      "weekday_4       731 non-null int64\n",
      "weekday_5       731 non-null int64\n",
      "weekday_6       731 non-null int64\n",
      "weathersit_1    731 non-null int64\n",
      "weathersit_2    731 non-null int64\n",
      "weathersit_3    731 non-null int64\n",
      "cnt             731 non-null float64\n",
      "log_cnt         731 non-null float64\n",
      "dtypes: float64(13), int64(26)\n",
      "memory usage: 222.8 KB\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression,Lasso,Ridge\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "df=pd.read_csv('FE_day.csv')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "features=['instant','casual','registered']\n",
    "df=df.drop(features,axis=1)\n",
    "\n",
    "X=df.drop('cnt',axis=1)\n",
    "y=df['cnt']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"red\"><b>题目3. 对全体数据，随机选择其中80%做训练数据，剩下20%为测试数据，评价指标为RMSE。（10分）</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">对训练数据和测试数据进行分离</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,Y_train,Y_test=train_test_split(X,y,test_size=0.2,random_state=42,shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(584, 35)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(147, 35)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"red\"><b>题目4. 用训练数据训练最小二乘线性回归模型（20分）、岭回归模型、Lasso模型，其中岭回归模型（30分）和Lasso模型（30分），注意岭回归模型和Lasso模型的正则超参数调优。</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">实例化回归模型</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr=LinearRegression()\n",
    "rr=Ridge()\n",
    "lsr=Lasso()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">回归模型训练</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,\n",
       "   normalize=False, positive=False, precompute=False, random_state=None,\n",
       "   selection='cyclic', tol=0.0001, warm_start=False)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(X_train,Y_train)\n",
    "rr.fit(X_train,Y_train)\n",
    "lsr.fit(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">回归模型预测</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_lr=lr.predict(X_test)\n",
    "y_pred_rr=rr.predict(X_test)\n",
    "y_pred_lsr=lsr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最小二乘线性回归对应的RMSE为0.163\n",
      "岭回归对应的RESE为0.161\n",
      "LASSO对应的RMSE为1.091\n"
     ]
    }
   ],
   "source": [
    "RMSE_lr=mean_squared_error(Y_test,y_pred_lr)\n",
    "RMSE_rr=mean_squared_error(Y_test,y_pred_rr)\n",
    "RMSE_lsr=mean_squared_error(Y_test,y_pred_lsr)\n",
    "print('最小二乘线性回归对应的RMSE为{:.3f}\\n岭回归对应的RESE为{:.3f}\\nLASSO对应的RMSE为{:.3f}'.format(RMSE_lr,RMSE_rr,RMSE_lsr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">根据结果可以看出岭回归对应的RMSE值最小，预测结果最为准确。<br>\n",
    "Lasso的预测结果精确度最低</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"red\"><b>题目5. 比较用上述三种模型得到的各特征的系数，以及各模型在测试集上的性能。并简单说明原因。（10分）</b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">比较三种模型的系数</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最小二乘线性回归的系数为：\n",
      "[ 2.17718692e-01 -8.51498329e+10 -2.36993247e+11  8.24203841e-02\n",
      " -2.40735784e-02 -3.43394081e-02 -4.04713481e-02  6.87658902e-03\n",
      " -1.69119485e+11 -1.69119485e+11 -1.69119485e+11 -1.69119485e+11\n",
      "  1.61726308e+11  1.61726308e+11  1.61726308e+11  1.61726308e+11\n",
      "  1.61726308e+11  1.61726308e+11  1.61726308e+11  1.61726308e+11\n",
      "  1.61726308e+11  1.61726308e+11  1.61726308e+11  1.61726308e+11\n",
      "  2.36518622e+10  5.33407873e+11  5.33407873e+11  5.33407873e+11\n",
      "  5.33407873e+11  5.33407873e+11  2.36518622e+10  3.38915992e+11\n",
      "  3.38915992e+11  3.38915992e+11  7.34013575e-01]\n",
      "截距为：-718489152733.2585\n",
      "岭回归的系数为：\n",
      "[ 2.19688922e-01 -4.85110328e-05 -7.47557489e-03  8.96591469e-02\n",
      " -1.67187621e-02 -3.59002220e-02 -4.10072066e-02  6.57062710e-03\n",
      " -4.76834215e-02  4.40071299e-02 -3.87038637e-02  4.23801553e-02\n",
      " -9.05817683e-02 -2.30354429e-01 -2.27788081e-02 -5.09801818e-02\n",
      "  5.29529169e-02  9.94089245e-02  2.95065304e-02  1.18951286e-01\n",
      "  2.43030052e-01  1.37867595e-01 -1.48290135e-01 -1.38731982e-01\n",
      " -6.49791179e-02 -4.65198188e-02 -1.68491043e-02  3.22177151e-02\n",
      "  2.75694395e-02  9.81579202e-05  6.84627286e-02  4.92391342e-02\n",
      " -6.44848696e-02  1.52457354e-02  7.26871086e-01]\n",
      "截距为：-0.01737733114449749\n",
      "Lasso的系数为：\n",
      "[ 0. -0.  0.  0.  0. -0. -0. -0. -0.  0.  0.  0. -0. -0. -0. -0.  0.  0.\n",
      "  0.  0.  0.  0. -0. -0. -0. -0. -0. -0.  0.  0.  0.  0. -0. -0.  0.]\n",
      "截距为：0.029252189333695656\n"
     ]
    }
   ],
   "source": [
    "print('最小二乘线性回归的系数为：\\n{}\\n截距为：{}'.format(lr.coef_,lr.intercept_))\n",
    "print('岭回归的系数为：\\n{}\\n截距为：{}'.format(rr.coef_,rr.intercept_))\n",
    "print('Lasso的系数为：\\n{}\\n截距为：{}'.format(lsr.coef_,lsr.intercept_))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">系数结果分析：<br>\n",
    "由这些系数可以看出，当alpha的值设为1时，由于正则项，系数大小对损失函数的结果影响很大，导致Lasso的所有系数均为0<br>\n",
    "这也是后面计算得到的Lasso的RMSE值很大的原因<br>\n",
    "而岭回归中由于有L2正则项具有系数收缩的作用，所以岭回归的系数与最小二乘相比，更趋近于0</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">修改超参数alpha的值</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha=0.01,岭回归系数为:\n",
      "[ 0.21796927  0.0007638  -0.00743822  0.08220871 -0.02343494 -0.03454365\n",
      " -0.04048822  0.00692919 -0.02710917  0.03895754 -0.05669411  0.04484573\n",
      " -0.12353514 -0.2648343  -0.03986166 -0.04881177  0.0631174   0.12156707\n",
      "  0.06514538  0.15217549  0.26571905  0.13434475 -0.1639876  -0.16103867\n",
      " -0.06556381 -0.04750148 -0.01616359  0.03255695  0.02891532 -0.00113775\n",
      "  0.06889436  0.04712263 -0.06707983  0.0199572   0.73368569]，\n",
      "截距为:-0.015175649159846687\n",
      "\n",
      "\n",
      "alpha=0.01,Lasso回归系数为:\n",
      "[ 0.17931302 -0.         -0.          0.10852407  0.         -0.01364788\n",
      " -0.02201655  0.         -0.0197398   0.          0.          0.\n",
      "  0.         -0.04467574  0.         -0.          0.          0.\n",
      " -0.          0.          0.03931017  0.04167531 -0.         -0.\n",
      " -0.         -0.         -0.          0.          0.         -0.\n",
      "  0.02226399  0.         -0.06385663  0.          0.79216423]，\n",
      "截距为:0.013864255981018456\n",
      "\n",
      "\n",
      "alpha=0.05,岭回归系数为:\n",
      "[ 2.18042031e-01  7.24612872e-04 -7.44311571e-03  8.26778924e-02\n",
      " -2.32097922e-02 -3.46104091e-02 -4.05141474e-02  6.91210264e-03\n",
      " -2.81550107e-02  3.92497820e-02 -5.57720273e-02  4.46772560e-02\n",
      " -1.21832566e-01 -2.63091426e-01 -3.89920520e-02 -4.89699070e-02\n",
      "  6.25644530e-02  1.20418202e-01  6.33219060e-02  1.50478482e-01\n",
      "  2.64592762e-01  1.34582087e-01 -1.63181805e-01 -1.59890136e-01\n",
      " -6.55366641e-02 -4.74537150e-02 -1.61999735e-02  3.25439842e-02\n",
      "  2.88500717e-02 -1.07974442e-03  6.88760411e-02  4.72147269e-02\n",
      " -6.69590382e-02  1.97443113e-02  7.33384433e-01]，\n",
      "截距为:-0.015276498028296736\n",
      "\n",
      "\n",
      "alpha=0.05,Lasso回归系数为:\n",
      "[ 0.12630728 -0.         -0.          0.06461246  0.         -0.\n",
      " -0.          0.         -0.          0.          0.          0.\n",
      " -0.         -0.         -0.         -0.          0.          0.\n",
      " -0.          0.          0.          0.         -0.         -0.\n",
      " -0.         -0.         -0.          0.          0.         -0.\n",
      "  0.          0.         -0.          0.          0.82537605]，\n",
      "截距为:-0.004315211450336785\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:9: UserWarning: With alpha=0, this algorithm does not converge well. You are advised to use the LinearRegression estimator\n",
      "  if __name__ == '__main__':\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\coordinate_descent.py:477: UserWarning: Coordinate descent with no regularization may lead to unexpected results and is discouraged.\n",
      "  positive)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\coordinate_descent.py:491: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Fitting data with very small alpha may cause precision problems.\n",
      "  ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "RMSE_rr1=[]\n",
    "RMSE_lsr1=[]\n",
    "for i in range(100):\n",
    "    i/=100\n",
    "    rr_1=Ridge(alpha=i)\n",
    "    lsr_1=Lasso(alpha=i)\n",
    "    \n",
    "    rr_1.fit(X_train,Y_train)\n",
    "    lsr_1.fit(X_train,Y_train)\n",
    "    \n",
    "    y_pred_rr1=rr_1.predict(X_test)\n",
    "    y_pred_lsr1=lsr_1.predict(X_test)\n",
    "    \n",
    "    RMSE_rr1.append([i,mean_squared_error(Y_test,y_pred_rr1)])\n",
    "    RMSE_lsr1.append([i,mean_squared_error(Y_test,y_pred_lsr1)])\n",
    "    if i ==0.05 or i == 0.01:\n",
    "        print('alpha={},岭回归系数为:\\n{}，\\n截距为:{}\\n\\n'.format(i,rr_1.coef_,rr_1.intercept_))\n",
    "        print('alpha={},Lasso回归系数为:\\n{}，\\n截距为:{}\\n\\n'.format(i,lsr_1.coef_,lsr_1.intercept_))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">由Lasso的回归系数可以知道，哪些特征对于模型训练更为重要一些。</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " [0.76, 0.1612811264922347],\n",
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       " [0.86, 0.16102315235539916],\n",
       " [0.87, 0.1609975995203963],\n",
       " [0.88, 0.1609720900500312],\n",
       " [0.89, 0.16094662367728516],\n",
       " [0.9, 0.160921200137819],\n",
       " [0.91, 0.16089581916993714],\n",
       " [0.92, 0.16087048051455433],\n",
       " [0.93, 0.16084518391515837],\n",
       " [0.94, 0.1608199291177793],\n",
       " [0.95, 0.16079471587095828],\n",
       " [0.96, 0.16076954392571058],\n",
       " [0.97, 0.16074441303549772],\n",
       " [0.98, 0.1607193229561954],\n",
       " [0.99, 0.16069427344606096]]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RMSE_rr1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " [0.9, 1.091131250587088],\n",
       " [0.91, 1.091131250587088],\n",
       " [0.92, 1.091131250587088],\n",
       " [0.93, 1.091131250587088],\n",
       " [0.94, 1.091131250587088],\n",
       " [0.95, 1.091131250587088],\n",
       " [0.96, 1.091131250587088],\n",
       " [0.97, 1.091131250587088],\n",
       " [0.98, 1.091131250587088],\n",
       " [0.99, 1.091131250587088]]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RMSE_lsr1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "plot1=plt.plot([x[0] for x in RMSE_rr1],[x[1] for x in RMSE_rr1],'r')\n",
    "plot2=plt.plot([x[0] for x in RMSE_lsr1],[x[1] for x in RMSE_lsr1],'b')\n",
    "plt.xlabel('alpha')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"4\" color=\"black\">图中，表示当alpha取值不同时，岭回归和Lasso对应的RMSE。蓝色的线是Lasso对应的RMSE,红色的线为岭回归对应的RMSE<br>\n",
    "从图上可以看出，当alpha不断减小的过程中，岭回归的对应的RMSE基本保持不变，而Lasso对应的RMSE快速下降，并最终的alpha=0时,与岭回归保持一致。<br>\n",
    "Lasso的RMSE的值急速下降的原因是在alpha减小的过程中，L1正则项的约束变小，所以等于0的系数的数量也不断减小，Lasso的结果更准确。</font>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
